NOVO Cloud · Microsoft Azure
The cloud foundation behind your AI, your apps, and your business.
Microsoft Azure deployed by NOVO Cloud — the AI/ML compute foundation purpose-built for what's next, and the secure cloud platform that runs your apps, your modernization workloads, and your business-critical infrastructure. Net-new cloud, hybrid extension, workload migration, AI infrastructure. Project-based deployment, modular scope.
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Why Microsoft Azure
Most growing businesses are running on infrastructure they wouldn't choose to build today. They built it years ago, when the choices were different.
The on-prem servers that need replacement on a depreciation schedule nobody likes. The data center contract that auto-renews if nobody fights it. Disaster recovery that's been theoretical for years because nobody's had time to test the failover. AWS or GCP environments accumulated by individual teams without coordination, generating cost reports nobody fully understands. AI ambitions stuck in pilot because the GPU compute isn't there and the data foundations aren't ready.
The consequences are predictable. Capital expenditure on hardware that depreciates faster than the business uses it. Data center costs without elasticity. Disaster recovery that hasn't been tested in eighteen months. AI workloads stuck in proof-of-concept. Modernization debt that compounds with every contract renewal.
Microsoft Azure is the alternative. The cloud platform built for hybrid reality, scaled for AI workloads, and architected to evolve as customer requirements change. Pay-for-what-you-use economics instead of capital expenditure cycles. Geographic distribution as architecture. Disaster recovery as configuration, not a quarterly fire drill.
What Cloud builds
Foundation, then workloads.
Every Azure engagement includes foundation work — landing zone architecture, identity, networking, security — plus the specific workloads the customer actually needs. NOVO Cloud handles both tiers as one integrated deployment, scaled to the customer's scope.
Tier 1 · Foundation layer (every Azure engagement)
Foundation 1
Landing zone architecture
Subscription topology, management groups, governance framework, policy baseline. Microsoft Cloud Adoption Framework reference architecture, applied — not just referenced. Designed for the customer's scale, compliance environment, and growth trajectory. The architectural foundation that determines whether the Azure environment ages well.
Foundation 2
Identity & access foundation
Microsoft Entra integration, Conditional Access policies, role-based access control, hybrid identity if the customer has on-premises Active Directory. Privileged Identity Management for administrative access. The control plane that secures everything else. Identity is the modern security perimeter.
Foundation 3
Network architecture
Hub-and-spoke topology, ExpressRoute or VPN connectivity to on-premises, network security groups, Azure Firewall design, segmentation between workloads. Network architecture that scales with workload growth rather than getting retrofitted later. DDoS protection, private endpoints, peering relationships designed deliberately.
Foundation 4
Security baseline
Microsoft Defender for Cloud baseline, Azure Key Vault for secrets and key management, encryption posture, compliance baselines configured for the customer's regulatory environment. Security configured as part of the foundation, not bolted on after workloads are running.
Tier 2 · Representative workloads (added per customer scope)
Workload 1
Azure Virtual Desktop (AVD)
Cloud-hosted virtual desktops at scale. Replace VDI infrastructure that's becoming expensive to maintain. Session host design, image management, FSLogix profiles, user assignment, scaling configuration. Multi-session Windows for cost efficiency where appropriate, dedicated hosts for workloads that require them. A common entry point for Azure deployment — desktop modernization that pays for itself within the first year for most customers.
Workload 2
Backup & disaster recovery
Azure Backup for workload protection, Azure Site Recovery for disaster recovery orchestration, geo-redundant DR architectures for business-critical workloads. RTO and RPO design tuned to actual business requirements rather than vendor defaults. Recovery testing built into the deployment, not deferred to “later.” A common entry point — replacing tape backup, on-prem DR sites, and the disaster recovery posture that hasn't been tested in years.
Workload 3
Hybrid infrastructure
Azure Arc, Azure Stack HCI, hybrid identity, on-premises extension. For customers with workloads that have to stay on-prem — compliance requirements, latency-sensitive operations, data sovereignty, cost considerations. Azure Arc brings Azure's management plane to on-prem and other cloud environments. Azure Stack HCI runs Azure services on customer hardware. Hybrid as architectural reality, not a transition state.
Workload 4 · Strategic
AI/ML infrastructure
Azure OpenAI Service, Azure AI Foundry, GPU compute, AI/ML workload patterns, data foundations for AI. The infrastructure customers building custom AI applications actually need. Strategic positioning — covered in detail in the next section.
These four are representative; Azure deployment scope adapts to customer requirements. NOVO has experience across the broader Azure platform — application modernization, database services, integration services, container platforms (AKS), and more. The engagement scope is determined by what the customer is trying to accomplish, not by a packaged service catalog.
How Cloud deploys it
Azure deployment is architecture work. Not provisioning.
Most Azure deployments end up as click-ops in the portal — provisioning resources as needed, accumulating sprawl, hitting cost surprises in month four, and discovering the architectural debt in year two when something needs to scale. NOVO Cloud's deployment work is what makes Azure actually behave as a cloud foundation rather than a collection of resources that drift over time.
Discipline 1
Landing zone discipline
Microsoft Cloud Adoption Framework landing zone applied as architecture, not template. Subscription topology designed for the customer's structure rather than copied from a reference diagram. Governance configured through Azure Policy so compliance is enforced rather than aspirational. Management groups, role assignments, naming conventions, tagging strategy — all set up as the deployment foundation. The work that determines whether the environment scales well or has to be redesigned in two years.
Discipline 2
Migration integrity
Migration from on-premises data centers, AWS, GCP, or other source environments. Workloads assessed for migration approach — lift-and-shift, refactor, or rebuild — based on actual workload characteristics rather than blanket strategy. Discovery and dependency mapping before migration runs. Migration validated for fidelity, performance, and cost before source environments are decommissioned.
Discipline 3
Operational readiness
Environment configured for handoff to operations from the start — whether that's NOVO Care or the customer's internal cloud team. Documentation complete: architecture, governance configuration, network design, security baselines, monitoring runbooks. FinOps baseline established with cost allocation, budget alerts, and optimization recommendations — Azure cost management as part of deployment, not a separate engagement after the bills surprise the customer.
Microsoft-architected Azure deployment
Microsoft Cloud Adoption Framework. Microsoft Well-Architected Framework. Microsoft landing zone reference architectures. NOVO follows Microsoft's published deployment frameworks rather than making up an in-house approach. Customers end up with environments that look like Microsoft's reference architectures because that's what they are.
- Microsoft Direct CSP Partner
- Microsoft Solutions Partner
Deployment accelerators
What NOVO brings gets you there faster — with nothing proprietary left behind.
NOVO has codified Azure deployment patterns into accelerators: landing zone deployment assets, Bicep and Terraform templates, migration playbooks, security baseline configurations, FinOps frameworks, and validation tooling. The accelerators are NOVO's tooling for delivering Azure efficiently — they aren't something the customer signs up for, locks into, or carries forward. What the customer ends up with is standard Azure, architected to Microsoft's published frameworks. No proprietary components embedded. No lock-in.
Azure as the AI/ML compute foundation
Azure isn't just where workloads run. It's where AI happens.
Modernization, hybrid extension, cost optimization, virtual desktop replacement — these are real outcomes, and they're usually the reason customers come to Azure in the first place. But Cloud builds Azure with another purpose in mind: enabling Azure to become the compute foundation where the customer's AI workloads run.
AI is happening in three places architecturally. Microsoft 365 Copilot grounds in M365 content and operates inside the productivity platform. Microsoft Teams hosts AI agents and voice AI as part of the communications platform. And custom AI — the workloads that go beyond packaged Microsoft AI products — runs on Azure. Azure OpenAI Service for foundation model access. Custom AI applications. AI/ML model training and inference. Agentic workflows that integrate line-of-business data.
01
AI/ML landing zone architecture
Microsoft's AI/ML landing zone reference architecture applied to the customer's environment. Subscription topology purpose-built for AI workloads — separation between development, model training, inference, and production. Governance and policy designed for AI scenarios specifically: model lifecycle management, data residency requirements, access patterns that traditional workload governance doesn't anticipate. The foundation that scales as the customer's AI usage matures from pilot to production.
02
Azure OpenAI Service deployment
Azure OpenAI Service deployed with proper access controls, content filtering, monitoring, audit logging, and cost governance. Private endpoints so model traffic doesn't cross the public internet. Quotas and rate limits configured for the customer's actual usage rather than defaults. Fine-tuning infrastructure where the customer needs custom models. The Azure OpenAI foundation customers actually build their own AI applications on, not the demo deployment.
03
Data foundations for AI
Data architectures that AI workloads actually need — Azure Data Lake for unstructured data, Azure AI Search for retrieval-augmented generation, vector databases for embedding storage, data pipelines for ingestion and transformation. Data classification, lineage, and access controls so AI workloads operate on data the customer controls and audits. The data plumbing without which AI is just an interesting demo.
04
AI workload security
Security architecture purpose-built for AI workloads. Model protection — preventing extraction, theft, or unauthorized fine-tuning. Prompt injection mitigation. Data exfiltration prevention through model interactions. Access auditing for who's invoking which models with what data. Content filtering aligned with the customer's compliance environment. The security posture AI workloads need that traditional workload security doesn't fully cover.
Cloud builds the Azure platform with this purpose in mind — the AI/ML compute foundation that custom AI runs on. Building the AI applications themselves — model selection, application development, agent design, training data curation, prompt engineering, AI program governance — is NOVO Compass's work. The compute foundation AI runs on is NOVO Cloud's.
Cloud builds. Care operates.
Cloud infrastructure isn't done at deploy. It's just started.
Microsoft Azure isn't a “deploy and walk away” engagement. The platform requires ongoing operations work — cost management, resource lifecycle, security monitoring, capacity management, configuration drift control, governance enforcement, FinOps optimization. That work is NOVO Care's job. The platform NOVO Cloud builds is the platform NOVO Care operates day-to-day.
NOVO Cloud · Builds
Microsoft Azure deployment
Project-based deployment. Foundation layer (landing zone, identity, network, security), workload layer (representative or customer-specific), AI/ML compute foundation.
NOVO Care · Operates
Day-to-day platform operations
Operational managed service. Cost management and FinOps, resource lifecycle, security monitoring, governance enforcement, capacity planning, configuration drift control. The same NOVO architectural team, in operations mode.
Customers can engage Cloud for Azure deployment without committing to Care for ongoing operations — that's a separate engagement decision. Most do engage Care, though, because cloud cost management alone usually pays for itself. One architectural commitment, two phases of work.
Ready when you are
The fastest way to know what your Azure deployment should look like is to talk through it.
Tell us about your current infrastructure reality — the on-prem servers approaching end of life, the data center contract coming up for renewal, the AWS environment that grew without coordination, the disaster recovery that hasn't been tested, the AI ambitions stuck on infrastructure that can't scale. We'll talk through what an Azure deployment would look like for your environment, what to prioritize, and how the handoff to ongoing operations would work.